Speaker
Abstract
AI has changed everything about software engineering...or has it? We've spent the past few decades learning how to build web-scale applications: complex, distributed systems that are too complex to fit into one reviewer's brain, but too critical to just YOLO into production. Over those decades, we've learned some lessons about where bugs proliferate, how to squash them, and how to balance safety and speed when nobody fully understands how the code works.
Today, every agent-authored codebase feels like the difficult-to-grok distributed systems of yesteryear. This talk highlights what we've learned about shipping complex systems safely, how those learnings can be repurposed to keep agents on the rails, and how AI can make cutting-edge correctness techniques mainstream.
$3,250, Conference (3 days). Current pricing ends November 20th. All pass options.
QCon San Francisco 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
Part of the track
Guardrails & Safety Nets for the New Landscape Hosted by Tanya Reilly Principal Engineer @Datadog, Author of "The Staff Engineer's Path"From the same track
Monday 16 November
10:35 Ballroom A Session Running Software Factory Efficiently at Uber Scale: Holding Agent Spend Steady While Requests Grew 9X Uday Kiran Medisetty VP, Distinguished Engineer @Uber At Uber, more than 70% of pull requests are attributed to coding agents. Engineers use more than 5K agent skills, and all MCP traffic goes through one gateway with more than 1,000 servers. 11:45 Ballroom A Session AI How Airbnb Guardrailed Its AI Customer Support Agent Weiping Peng Distinguished Engineer @Airbnb, Previously Principal Architect @Salesforce for AI platform When Airbnb launched its AI customer support assistant, the feature made the news — the guardrails built to make it safe to ship did not. Yet an AI agent that talks to millions of customers, remembers a conversation across turns, and can trigger account actions is a… 13:35 Ballroom A Session LLM Flip-Flops: From Reliability Risk to a Hill-Climbing Signal Diane Lin Staff Engineer @Datadog Run the same task through the same LLM twice, and you may get two materially different answers. This behavior is often dismissed as the stochastic nature of LLMs, but it creates a serious product risk. 14:45 Seacliff D Unconference Unconference: Guardrails & Safety Nets 15:55 Ballroom A Session Agentic Trust: Securing AI Agents in Production Amanda Walker Sr. Director, Engineering - Privacy, Safety and Security @Google This session will cover practical measures that you can take now to run agents more securely in production. This will not cover topics like model training and alignment; rather it will focus on deploying an existing agent as safely as possible. 17:05 Ballroom A Session Into the Labyrinth: What Distributed Systems Have Taught Us About Guardrails Akshay Shah Field CTO @Antithesis AI has changed everything about software engineering...or has it? We've spent the past few decades learning how to build web-scale applications: complex, distributed systems that are too complex to fit into one reviewer's brain, but too critical to just YOLO into production.